Machine Learning isn’t necessarily a new trend. But, with the growth of data volumes over the past few years, the algorithms employed by Machine Learning technologies have become ever more important. According to Darryl K. Taft it “is helping, with software engineers continually creating and improving algorithms that automatically analyze data to identify patterns and predict outcomes. Machine learning involves studying computer algorithms that provide computer programs with the ability to learn, discover, predict and improve automatically using large amounts of data without explicit programming, said Dave Schubmehl, research director for Cognitive Systems and Content Analytics at IDC.”
“Machine learning starts with data—the more you have, the better your results are likely to be,” said David Chappell, in a white paper on Microsoft’s Azure Machine Learning solution. “Because we live in the big data era, machine learning has become much more popular in the last few years. Having lots of data to work with in many different areas lets the techniques of machine learning be applied to a broader set of problems. Since the process starts with data, choosing the right data to work with is critically important.”
He continues with, “although machine learning libraries have been around for decades and have been offered as part of many statistical packages, including IBM’s SPSS, SAS and many others, the use of machine learning by enterprises has not been widespread until recently. “